In this blog post, we’ll take a closer look at a feature of the SIMCA data analytics software called the Omics skin. So what exactly is an “omics” skin?
In this blog post we will take a closer look at OPLS*, or Orthogonal PLS, a method to model process data. The advantage of OPLS compared to PLS is that you can uncover hidden details and get a more precise understanding of your data – all of which will help you build better predictive models of your processes.
Worldwide demand for energy escalates every year, and the consumption of fossil fuels continues to increase despite the growing supply of alternative energy options. Globally, about 81 percent of energy comes from a finite supply of fossil fuels like oil, coal and natural gas. Fossil fuels are used to heat homes, run vehicles, power industry and manufacturing, and provide electricity.
An important environmental issue that has come into focus is the increasing number of chemicals that we are exposed to in our everyday life. Chemicals are found in products ranging from cars and furniture to clothing and skincare, and are also by-products from combustion. The CAS REGISTRYSM, an international standard for chemical information, currently contains more than 134 million unique organic and inorganic chemical substances and more than 67 million sequences.
Analyzing batch process data is a lot like juggling. You have multiple sets of data from different sources and in order to turn them into a meaningful presentation, you need a method of handling them to make sure they are all in the right place at the right time.
When to apply OPLS-DA vs PCA for metabolomics and other omics data analysis
Do you know when to use OPLS-DA and when to use PCA/SIMCA data analysis techniques? Find out how to uncover the differences in your data with these classification and discriminant analysis methods.
Whether you work in engineering, R&D, or a science lab, understanding the basics of experimental design can help you achieve more statistically optimal results from your experiments or improve your output quality.